Neda Azarmehr

Hi @Catosine, I have got the below genotypes from DARTS for ultrasound dataset after training for 10 epochs. I was wondering why genotypes were similar during epochs 1 to 10,...

Hi @Catosine, Thanks a lot for explanation. Regarding the second question, I still struggle to understand it. What I understood in normal cell the green box c_{k-1} is output cell...

Hi @Catosine, Thank you for the reply. As you said, normal cell would keep the input and output have exactly the same shape. So, I'm wondering why I have max_pool...

Hi @karanchahal, I assume is very depends on the dataset size. In my case was about 10 hours on Colab for 600 images (training and validation).

Hi @Catosine, Thanks a lot for answering the question. I have few more questions, I really appreciate if you could help to clarify these. 1. Regarding DARTS paper figure 1.b,...

Thanks a lot for your explanation. All your explanations are really helpful. Greatly appreciated. about question 1: > but it is NOT THE SAME as cells used to search. Based...

Hi @Catosine Thank you for all your explanation so far. I have some questions as follows: 1. I was worry that why `model.genotype()` in `train_search.py` is not evolving and it's...

Hi @Catosine Thank you for your reply. > 1. Would you mind show me the genotypes? Here is the genotype found during 25 epochs for CIFAR10 dataset (means model.gentype() was...

Hi @Catosine Thanks a lot for the explanation. genotype.model() is evolving now for my dataset when --unrolled = true otherwise will give me the same genotypes. How can I justify...

Hi @Catosine , Could you please give a brief explanation of what unrolled does here? should it be always False?